abacusai.prediction_operator

Classes

`CodeSource`	Code source for python-based custom feature groups and models
`PredictionOperatorVersion`	A prediction operator version.
`RefreshSchedule`	A refresh schedule for an object. Defines when the next version of the object will be created
`AbstractApiClass`
`PredictionOperator`	A prediction operator.

Module Contents

class abacusai.prediction_operator.CodeSource(client, sourceType=None, sourceCode=None, applicationConnectorId=None, applicationConnectorInfo=None, packageRequirements=None, status=None, error=None, publishingMsg=None, moduleDependencies=None)

Bases: abacusai.return_class.AbstractApiClass

Code source for python-based custom feature groups and models

Parameters:

client (ApiClient) – An authenticated API Client instance
sourceType (str) – The type of the source, one of TEXT, PYTHON, FILE_UPLOAD, or APPLICATION_CONNECTOR
sourceCode (str) – If the type of the source is TEXT, the raw text of the function
applicationConnectorId (str) – The Application Connector to fetch the code from
applicationConnectorInfo (str) – Args passed to the application connector to fetch the code
packageRequirements (list) – The pip package dependencies required to run the code
status (str) – The status of the code and validations
error (str) – If the status is failed, an error message describing what went wrong
publishingMsg (dict) – Warnings in the source code
moduleDependencies (list) – The list of internal modules dependencies required to run the code

__repr__(): Return repr(self).

to_dict()

Get a dict representation of the parameters in this class

Returns:: The dict value representation of the class parameters
Return type:: dict

import_as_cell(): Adds the source code as an unexecuted cell in the notebook.

class abacusai.prediction_operator.PredictionOperatorVersion(client, predictionOperatorId=None, predictionOperatorVersion=None, createdAt=None, updatedAt=None, sourceCode=None, memory=None, useGpu=None, featureGroupIds=None, featureGroupVersions=None, status=None, error=None, codeSource={})

Bases: abacusai.return_class.AbstractApiClass

A prediction operator version.

Parameters:

client (ApiClient) – An authenticated API Client instance
predictionOperatorId (str) – The unique identifier of the prediction operator.
predictionOperatorVersion (str) – The unique identifier of the prediction operator version.
createdAt (str) – Date and time at which the prediction operator was created.
updatedAt (str) – Date and time at which the prediction operator was updated.
sourceCode (str) – Python code used to make the prediction operator.
memory (int) – Memory in GB specified for the prediction operator version.
useGpu (bool) – Whether this prediction operator version is using gpu.
featureGroupIds (list) – A list of Feature Group IDs used for initializing.
featureGroupVersions (list) – A list of Feature Group version IDs used for initializing.
status (str) – The current status of the prediction operator version.
error (str) – The error message if the status failed.
codeSource (CodeSource) – If a python model, information on the source code.

__repr__(): Return repr(self).

to_dict()

Get a dict representation of the parameters in this class

Returns:: The dict value representation of the class parameters
Return type:: dict

delete()

Delete a prediction operator version.

Parameters:: prediction_operator_version (str) – The unique ID of the prediction operator version.

class abacusai.prediction_operator.RefreshSchedule(client, refreshPolicyId=None, nextRunTime=None, cron=None, refreshType=None, error=None)

Bases: abacusai.return_class.AbstractApiClass

A refresh schedule for an object. Defines when the next version of the object will be created

Parameters:

client (ApiClient) – An authenticated API Client instance
refreshPolicyId (str) – The unique identifier of the refresh policy
nextRunTime (str) – The next run time of the refresh policy. If null, the policy is paused.
cron (str) – A cron-style string that describes the when this refresh policy is to be executed in UTC
refreshType (str) – The type of refresh that will be run
error (str) – An error message for the last pipeline run of a policy

__repr__(): Return repr(self).

to_dict()

Get a dict representation of the parameters in this class

Returns:: The dict value representation of the class parameters
Return type:: dict

class abacusai.prediction_operator.AbstractApiClass(client, id)

__eq__(other): Return self==value.

_get_attribute_as_dict(attribute)

class abacusai.prediction_operator.PredictionOperator(client, name=None, predictionOperatorId=None, createdAt=None, updatedAt=None, projectId=None, predictFunctionName=None, sourceCode=None, initializeFunctionName=None, notebookId=None, memory=None, useGpu=None, featureGroupIds=None, featureGroupTableNames=None, codeSource={}, refreshSchedules={}, latestPredictionOperatorVersion={})

Bases: abacusai.return_class.AbstractApiClass

A prediction operator.

Parameters:

client (ApiClient) – An authenticated API Client instance
name (str) – The name for the prediction operator.
predictionOperatorId (str) – The unique identifier of the prediction operator.
createdAt (str) – Date and time at which the prediction operator was created.
updatedAt (str) – Date and time at which the prediction operator was updated.
projectId (str) – The project this prediction operator belongs to.
predictFunctionName (str) – Name of the function found in the source code that will be executed to run predictions.
sourceCode (str) – Python code used to make the prediction operator.
initializeFunctionName (str) – Name of the optional initialize function found in the source code. This function will generate anything used by predictions, based on input feature groups.
notebookId (str) – The unique string identifier of the notebook used to create or edit the prediction operator.
memory (int) – Memory in GB specified for the prediction operator.
useGpu (bool) – Whether this prediction operator is using gpu.
featureGroupIds (list) – A list of Feature Group IDs used for initializing.
featureGroupTableNames (list) – A list of Feature Group table names used for initializing.
codeSource (CodeSource) – If a python model, information on the source code.
latestPredictionOperatorVersion (PredictionOperatorVersion) – The unique string identifier of the latest version.
refreshSchedules (RefreshSchedule) – List of refresh schedules that indicate when the next prediction operator version will be processed

__repr__(): Return repr(self).

to_dict()

Get a dict representation of the parameters in this class

Returns:: The dict value representation of the class parameters
Return type:: dict

refresh()

Calls describe and refreshes the current object’s fields

Returns:: The current object
Return type:: PredictionOperator

describe()

Describe an existing prediction operator.

Parameters:: prediction_operator_id (str) – The unique ID of the prediction operator.
Returns:: The requested prediction operator object.
Return type:: PredictionOperator

update(name=None, feature_group_ids=None, source_code=None, initialize_function_name=None, predict_function_name=None, cpu_size=None, memory=None, package_requirements=None, use_gpu=None)

Update an existing prediction operator.

Parameters:

name (str) – Name of the prediction operator.
feature_group_ids (List) – List of feature groups that are supplied to the initialize function as parameters. Each of the parameters are materialized Dataframes. The order should match the initialize function’s parameters.
source_code (str) – Contents of a valid Python source code file. The source code should contain the function predictFunctionName, and the function ‘initializeFunctionName’ if defined.
initialize_function_name (str) – Name of the optional initialize function found in the source code. This function will generate anything used by predictions, based on input feature groups.
predict_function_name (str) – Name of the function found in the source code that will be executed to run predictions.
cpu_size (str) – Size of the CPU for the prediction operator.
memory (int) – Memory (in GB) for the prediction operator.
package_requirements (list) – List of package requirement strings. For example: [‘numpy==1.2.3’, ‘pandas>=1.4.0’]
use_gpu (bool) – Whether this prediction operator needs gpu.

Returns:

The updated prediction operator object.

Return type:

PredictionOperator

delete()

Delete an existing prediction operator.

Parameters:: prediction_operator_id (str) – The unique ID of the prediction operator.

deploy(auto_deploy=True)

Deploy the prediction operator.

Parameters:: auto_deploy (bool) – Flag to enable the automatic deployment when a new prediction operator version is created.
Returns:: The created deployment object.
Return type:: Deployment

create_version()

Create a new version of the prediction operator.

Parameters:: prediction_operator_id (str) – The unique ID of the prediction operator.
Returns:: The created prediction operator version object.
Return type:: PredictionOperatorVersion

list_versions()

List all the prediction operator versions for a prediction operator.

Parameters:: prediction_operator_id (str) – The unique ID of the prediction operator.
Returns:: A list of prediction operator version objects.
Return type:: list[PredictionOperatorVersion]